research Scalp Disease Analysis Using Deep Learning Models
Deep learning models can analyze scalp diseases effectively.
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30 / 1000+ results research Deep Learning-Based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia
A deep learning model accurately predicts male hair loss types using scalp images.
research Investigating Different Deep Learning Models for Classification of Folliculitis
GoogLeNet is the best model for identifying folliculitis.
research Deep Learning Model to Predict Sentinel Lymph Node Status in Melanoma Patients
The AI model somewhat predicts lymph node status in melanoma patients using skin sample images.
research Enhanced Hair Disease Classification Using Deep Learning
The model accurately classifies hair conditions with 97% accuracy.
research Deep Learning-Based Automatic System for Diagnosis and Classification of Skin Dermatoses
The document concludes that an automatic system using deep learning can help diagnose skin disorders, but challenges and opportunities in this area remain.
research Optimizing Skin Disease Diagnosis: Harnessing Online Community Data With Contrastive Learning and Clustering Techniques
Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
research Hair and Scalp Disease Detection Using Machine Learning and Image Processing
The machine learning model accurately detected hair loss and scalp diseases using processed images.
research Evaluation of Automated Measurement of Hair Density Using Deep Neural Networks
Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.
research Leveraging Deep Neural Networks to Uncover Unprecedented Levels of Precision in the Diagnosis of Hair and Scalp Disorders
A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
research Inferring Spatially Resolved Transcriptomics Data from Whole Slide Images for the Assessment of Colorectal Tumor Metastasis: A Feasibility Study
Using deep learning to predict gene expression from images could help assess colorectal cancer metastasis.
research Detecting Shortcut Learning for Fair Medical AI Using Shortcut Testing
The ShorT method can detect and help reduce bias in medical AI by identifying shortcut learning.
research How Good Is Artificial Intelligence at Solving Hairy Problems? A Review of AI Applications in Hair Restoration and Hair Disorders
AI is effective in diagnosing and treating hair disorders, including detecting hair loss and scalp conditions with high accuracy, but it should supplement, not replace, doctor-patient interactions.
research Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
research Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study
Machine learning can predict symptoms and quality of life in chronic skin disease patients using smartphone app data, and shows that app use varies with patient characteristics.
research Classification Framework for Healthy Hair and Alopecia Areata: A Machine Learning Approach
Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
research Hair Disease Classification Using Convolutional Neural Network Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
research Enhancing Hairfall Prediction: A Comparative Analysis of Individual Algorithms and an Ensemble Method
Combining multiple algorithms predicts hair fall more accurately than using single algorithms.
research Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.
research Hair Cluster Detection Model Based on Dermoscopic Images
The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
research Aspect-Level Drug Reviews Sentiment Analysis Based on Double BiGRU and Knowledge Transfer
A model called PM-DBiGRU was developed for analyzing sentiments in drug reviews, and it performed better than other models, but struggled with complex sentences and situations requiring background knowledge.
research Drug Repurposing Against KRAS Mutant G12C: A Machine Learning, Molecular Docking, and Molecular Dynamics Study
Afatinib, neratinib, and zanubrutinib could be effective against KRASG12C-mutant tumors.
research Generative Adversarial Networks for Anonymous Acneic Face Dataset Generation
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
research Androgen Signaling Regulates SARS-CoV-2 Receptor Levels and Is Associated with Severe COVID-19 Symptoms in Men
Male hormones affect COVID-19 severity and certain drugs targeting these hormones could help reduce the risk.
research Autonomous Robotic Surgery: Has the Future Arrived?
Autonomous robotic surgery is advancing but still requires human supervision for complex procedures.
research Impact of Artificial Intelligence on Healthcare
AI is revolutionizing healthcare by improving diagnosis, treatment, and monitoring, but still needs close supervision.
research Crystal Structure of Steroid Reductase SRD5A Reveals Conserved Steroid Reduction Mechanism
The structure of SRD5A reveals how it reduces steroids, aiding drug design for related health conditions.
research The Microanatomy of Human Skin in Aging
Aging skin shows thinner layers, fewer hair follicles, and new biomarkers like increased space between cells and smaller sebaceous glands.
research Diagnosis, Manifestations, Laboratory Investigations, and Prognosis in Pediatric and Adult Cushing’s Disease in a Large Center in China
Children and adults with Cushing's disease show different symptoms and males have more severe cases; surgery outcomes can be predicted by certain factors.
research Trend and Co-Occurrence Network of COVID-19 Symptoms From Large-Scale Social Media Data: Infoveillance Study
Social media data can help track and predict COVID-19 symptoms and trends.